Multiple measurement mode in a physiological sensor

ABSTRACT

In a physiological sensor that estimates a true parameter value by providing a predicted parameter value, multiple measurements are taken to increase the accuracy of the predicted parameter value. The sensor can be reapplied between measurements to decrease the probability of an erroneous prediction caused by sensor misplacement. Some measurements can be discarded before calculating a predicted parameter value. The physiological sensor can have a plurality of modes, with one of the modes corresponding to multiple measurement process.

PRIORITY CLAIM

This application claims priority benefit under 35 U.S.C. §119 toprovisional application Ser. No. 61/507,469 filed Jul. 13, 2011. Thedisclosure of this prior application is hereby incorporated by referencein its entirety and should be considered a part of this application.

BACKGROUND

Spectroscopy is a common technique for measuring the concentration oforganic and some inorganic constituents of a solution. The theoreticalbasis of this technique is the Beer-Lambert law, which states that theconcentration c_(i) of an absorbent in solution can be determined by theintensity of light transmitted through the solution, knowing thepathlength the intensity of the incident light I_(0,λ), and theextinction coefficient ε_(i,λ) at a particular wavelength λ. Ingeneralized form, the Beer-Lambert law is expressed as:

$\begin{matrix}{I_{\lambda} = {I_{0,\lambda}^{{- d_{\lambda}} \cdot \mu_{a,\lambda}}}} & (1) \\{\mu_{a,\lambda} = {\sum\limits_{i = 1}^{n}{ɛ_{i,\lambda} \cdot c_{i}}}} & (2)\end{matrix}$

where, μ_(0,λ) is the bulk absorption coefficient and represents theprobability of absorption per unit length. The minimum number ofdiscrete wavelengths that are required to solve EQS. 1-2 are the numberof significant absorbers that are present in the solution.

A practical application of this technique is pulse oximetry, whichutilizes a noninvasive sensor to measure oxygen saturation (SpO₂) andpulse rate. The sensor has light emitting diodes (LEDs) that transmitoptical radiation of red and infrared wavelengths into a tissue site anda detector that responds to the intensity of the optical radiation afterabsorption by pulsatile arterial blood flowing within the tissue site.Based on this response, a processor determines measurements for SpO₂,pulse rate, and can output representative plethysmographic waveforms.Thus, “pulse oximetry” as used herein encompasses its broad ordinarymeaning known to one of skill in the art, which includes at least thosenoninvasive procedures for measuring parameters of circulating bloodthrough spectroscopy. Moreover, “plethysmograph” as used herein(commonly referred to as “photoplethysmograph,”) encompasses its broadordinary meaning known to one of skill in the art, which includes atleast data representative of a change in the absorption of particularwavelengths of light as a function of the changes in body tissueresulting from pulsing blood.

Pulse oximeters capable of reading through motion induced noise areavailable from Masimo Corporation (“Masimo”) of Irvine, Calif. Moreover,portable and other oximeters capable of reading through motion inducednoise are disclosed in at least U.S. Pat. Nos. 6,770,028, 6,658,276,6,584,336, 6,263,222, 6,157,850, 5,769,785, and 5,632,272, which areowned by Masimo, and are incorporated by reference herein. Such readingthrough motion oximeters have gained rapid acceptance in a wide varietyof medical applications, including surgical wards, intensive care andneonatal units, general wards, home care, physical training, andvirtually all type of monitoring scenarios.

SUMMARY OF THE INVENTION

In a physiological sensor that estimates a true parameter value byproviding a predicted parameter value, multiple measurements are takento increase the accuracy of the predicted parameter value. To decreasethe probability of an erroneous prediction caused by sensormisplacement, the sensor can be reapplied between measurements. Somemeasurements can be discarded before calculating a predicted parametervalue.

In one embodiment, a physiological sensor makes blood absorptionmeasurements at a plurality of wavelengths. Blood absorptionmeasurements are made multiple times and the sensor is reapplied betweenmeasurements. This helps increase the accuracy of the predictedparameter value and decrease the probability of an erroneous predictioncaused by sensor misplacement. The results of each measurement are usedto calculate a predicted parameter value corresponding to themeasurement. Some of the calculated predicted parameter values can bediscarded before averaging the remaining values to obtain a finalpredicted parameter value. The final predicted parameter value isprovided to the user.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a block diagram of an example data collection systemcapable of noninvasively measuring one or more blood analytes in amonitored patient, according to an embodiment of the disclosure;

FIG. 2 illustrates an exemplary handheld monitor and an exemplarynoninvasive optical sensor of the patient monitoring system of FIG. 1,according to embodiments of the disclosure;

FIG. 3 illustrates a block diagram of a multiple measurement process;

FIG. 4 illustrates a block diagram of a predicted parameter calculationprocess; and

FIG. 5 illustrates a block diagram of a dual mode sensor measurementprocess.

DETAILED DESCRIPTION Single Measurement Example

A multiple wavelength sensor and a noninvasive multi-parameter patientmonitor can make blood absorption measurements at a plurality ofwavelengths. For example, blood absorption measurements can be made ateight wavelengths. Advantageously, this rich wavelength data, comparedwith conventional pulse oximetry, allows a determination of a tissueprofile or tissue characterization over a wavelength spectrum.

Multiple Measurement Mode

In a physiological sensor, measurements can be affected by wide varietyof environmental factors. In pulse oximetry, these factors can includetemperature, altitude, blood perfusion, sensor placement, and othersubstances in the blood. In particular, sensor placement can have asignificant effect on the accuracy of predicted parameter values.Fortunately, sensor placement often can be controlled and adjusted.Unfortunately, it is hard to determine whether a sensor is optimallyplaced or whether the measurement could benefit from adjustment of thesensor position.

To increase the accuracy of a predicted parameter value, multiplemeasurements can be taken. Each measurement can yield a distinct set ofinput values, and each set of input values can produce by calculation acorresponding predicted parameter value. In pulse oximetry, the opticalsensor can be reapplied between the measurements to decrease theprobability of an erroneous measurement due to improper sensorplacement. Optionally, some of the measurements and correspondingpredicted parameter values can be discarded. Also optionally, some ofthe measurements or predicted parameter values can be averaged. Theresulting predicted parameter value or values can be displayed to theuser.

In one embodiment, at least three separate measurements are taken by aphysiological sensor. As will be understood from the disclosure herein,addition measurements can also be taken. During each of the three ormore measurements, blood absorption measurements are made at a pluralityof wavelengths. The rich wavelength data from each measurement providesa set of input values that can be used to calculate a predictedparameter value for that measurement. After each of the first and secondmeasurements, the sensor can be adjusted or removed and replaced. Theuser can be prompted to remove and replace the sensor using visual,audio, or physical cues, and the measurement process can be suspendeduntil the sensor is replaced. In some embodiments, the user can indicatethat the sensor has been replaced by pressing a button or tapping atouch screen.

After all three measurements have been obtained, for each measurement,the measurement's set of input values can be used to calculate for thatmeasurement a predicted parameter value. From these three predictedparameter values (corresponding to the three distinct measurements), themedian predicted parameter value can be selected and averaged with thenext closest predicted parameter value. For example, if the predictedparameter values are 88, 89, and 96, the median value, 89, can beaveraged with the next closest value, 88. The average of these twovalues, 88.5, can be reported as the predicted parameter value. Theresult can be displayed to the user.

In some embodiments, more than three measurements can be taken and morethan one predicted parameter value can be dropped. In other embodiments,various known statistical techniques, such as outlier detectionalgorithms, can be used to select from among the predicted parametervalues the predicted parameter value that best characterizes thedistribution of parameter values. The selected parameter value can beprovided as the final predicted parameter value. In still otherembodiments, measurements are selected to be discarded based on themeasured input values rather than the predicted parameter values. Forexample, the mean or median measured input value can be determined, andone or more input values furthest from that determined value can bediscarded. Predicted parameter values can be determined for theremaining input values, and the predicted parameter values can beaveraged to obtain a final predicted parameter value. Additionally,measurements can be dropped based on a confidence determination of themeasurements. For example, in a system configured to take threemeasurements, if one measurement is found to have low confidence, thatmeasurement can be dropped and the device can instruct the user or caregiver to take a fourth measurement. Additional measurements can also betaken until all three measurements have an adequate confidencedetermination.

Example Embodiment of A Physiological Sensor With Two Modes

In one embodiment, a physiological sensor can have two or more operatingmodes. Two of the operating modes can be normal and multi modes. Theoperating mode can be selected by the user before the measurementprocess begins. The user can be prompted with instructions for theselected mode.

In normal mode, a true parameter value is estimated by providing apredicted parameter value based on a measured set of input values. Thismode can be useful where a quick estimate of a predicted parameter valueis needed. In multi mode, successive measurements can be taken asdescribed above in the Multiple Measurement Mode section. For example,three separate input values can be measured, and the sensor can bereapplied between measurements. A predicted parameter value can becalculated for each of the measured input values. Optionally, one ormore of the predicted parameter values can be dropped and the remainingvalues can be averaged to yield a final prediction. For example, ofthree predicted parameter values, the median value can be averaged withthe next closest value and provided to the user. The multi-mode canprovide a more accurate measurement with a higher confidence than thenormal mode.

Reference will now be made to the Figures to discuss embodiments of thepresent disclosure.

FIG. 1 illustrates an example of a data collection system 100. Incertain embodiments, the data collection system 100 noninvasivelymeasure a blood analyte, such as oxygen, carbon monoxide, methemoglobin,total hemoglobin, glucose, proteins, glucose, lipids, a percentagethereof (e.g., saturation) or for measuring many other physiologicallyrelevant patient characteristics. The system 100 can also measureadditional blood analytes and/or other physiological parameters usefulin determining a state or trend of wellness of a patient.

The data collection system 100 can be capable of measuring opticalradiation from the measurement site. For example, in some embodiments,the data collection system 100 can employ photodiodes defined in termsof area. In an embodiment, the area is from about 1 mm2-5 mm2 (orhigher) that are capable of detecting about 100 nanoamps (nA) or less ofcurrent resulting from measured light at full scale. In addition tohaving its ordinary meaning, the phrase “at full scale” can mean lightsaturation of a photodiode amplifier (not shown). Of course, as would beunderstood by a person of skill in the art from the present disclosure,various other sizes and types of photodiodes can be used with theembodiments of the present disclosure.

The data collection system 100 can measure a range of approximatelyabout 2 nA to about 100 nA full scale. The data collection system 100can also include sensor front-ends that are capable of processing andamplifying current from the detector(s) at signal-to-noise ratios (SNRs)of about 100 decibels (dB) or more, such as about 120 dB in order tomeasure various desired analytes. The data collection system 100 canoperate with a lower SNR if less accuracy is desired for an analyte likeglucose.

The data collection system 100 can measure analyte concentrations,including glucose, at least in part by detecting light attenuated by ameasurement site 102. The measurement site 102 can be any location on apatient's body, such as a finger, foot, ear lobe, or the like. Forconvenience, this disclosure is described primarily in the context of afinger measurement site 102. However, the features of the embodimentsdisclosed herein can be used with other measurement sites 102, or with aplurality of measurement sites for multiple measurements.

In the depicted embodiment, the system 100 includes an optional tissuethickness adjuster or tissue shaper 105, which can include one or moreprotrusions, bumps, lenses, or other suitable tissue-shaping mechanisms.In certain embodiments, the tissue shaper 105 is a flat or substantiallyflat surface that can be positioned proximate the measurement site 102and that can apply sufficient pressure to cause the tissue of themeasurement site 102 to be flat or substantially flat. In otherembodiments, the tissue shaper 105 is a convex or substantially convexsurface with respect to the measurement site 102. Many otherconfigurations of the tissue shaper 105 are possible. Advantageously, incertain embodiments, the tissue shaper 105 reduces thickness of themeasurement site 102 while preventing or reducing occlusion at themeasurement site 102. Reducing thickness of the site can advantageouslyreduce the amount of attenuation of the light because the there is lesstissue through which the light must travel. Shaping the tissue in to aconvex (or alternatively concave) surface can also provide more surfacearea from which light can be detected.

The embodiment of the data collection system 100 shown also includes anoptional noise shield 103. In an embodiment, the noise shield 103 can beadvantageously adapted to reduce electromagnetic noise while increasingthe transmittance of light from the measurement site 102 to one or moredetectors 106 (described below). For example, the noise shield 103 canadvantageously include a conductive coated glass or metal gridelectrically communicating with one or more other shields of the sensor101. In an embodiment where the noise shield 103 includes conductivecoated glass, the coating can advantageously include indium tin oxide.In an embodiment, the indium tin oxide includes a surface resistivityranging from approximately from 30 ohms per square inch to 500 ohms persquare inch. In an embodiment, the resistivity is approximately 30, 200,or 500 ohms per square inch. As would be understood by a person of skillin the art from the present disclosure, other resistivities can also beused which are less than 30 ohms or more than 500 ohms. Other conductivematerials transparent or substantially transparent to light can be usedinstead.

In some embodiments, the measurement site 102 is somewhere along anon-dominant arm or a non-dominant hand, e.g., a right-handed person'sleft arm or left hand. In some patients, the non-dominant arm or handcan have less musculature and higher fat content, which can result inless water content in that tissue of the patient. Tissue having lesswater content can provide less interference with the particularwavelengths that are absorbed in a useful manner by blood analytes likeglucose. Accordingly, in some embodiments, the data collection system100 can be used on a person's non-dominant hand or arm.

In some embodiments, measurements are made multiple times and the sensoris reapplied to between measurements, either to the original measurementsite or to an additional measurement site. The results of eachmeasurement may be used to calculate a predicted parameter valuecorresponding to the measurement. Taking multiple measurements mayincrease the accuracy of the data collected, and reapplying the sensorto the measurement site or a new measurement site may decrease theprobability of an erroneous prediction caused by sensor misplacement.

The data collection system 100 can include a sensor 101 (or multiplesensors) that is coupled to a processing device or physiological monitor109. In an embodiment, the sensor 101 and the monitor 109 are integratedtogether into a single unit. In another embodiment, the sensor 101 andthe monitor 109 are separate from each other and communicate one withanother in any suitable manner, such as via a wired or wirelessconnection. The sensor 101 and monitor 109 can be attachable anddetachable from each other for the convenience of the user or caregiver,for ease of storage, sterility issues, or the like. The sensor 101 andthe monitor 109 will now be further described.

In the depicted embodiment shown in FIG. 1, the sensor 101 includes anemitter 104, a tissue shaper 105, a set of detectors 106, and afront-end interface 108. The emitter 104 can serve as the source ofoptical radiation transmitted towards measurement site 102. As will bedescribed in further detail below, the emitter 104 can include one ormore sources of optical radiation, such as LEDs, laser diodes,incandescent bulbs with appropriate frequency-selective filters,combinations of the same, or the like. In an embodiment, the emitter 104includes sets of optical sources that are capable of emitting visibleand near-infrared optical radiation.

In some embodiments, the emitter 104 is used as a point optical source,and thus, the one or more optical sources of the emitter 104 can belocated within a close distance to each other, such as within about a 2mm to about 4 mm. The emitters 104 can be arranged in an array, such asis described in U.S. Publication No. 2006/0211924, filed Sep. 21, 2006,titled “Multiple Wavelength Sensor Emitters,” the disclosure of which ishereby incorporated by reference in its entirety. In particular, theemitters 104 can be arranged at least in part as described in paragraphs[0061] through [0068] of the aforementioned publication, whichparagraphs are hereby incorporated specifically by reference. Otherrelative spatial relationships can be used to arrange the emitters 104.

For analytes like glucose, currently available non-invasive techniquesoften attempt to employ light near the water absorbance minima at orabout 1600 nm. Typically, these devices and methods employ a singlewavelength or single band of wavelengths at or about 1600 nm. However,to date, these techniques have been unable to adequately consistentlymeasure analytes like glucose based on spectroscopy.

In contrast, the emitter 104 of the data collection system 100 can emit,in certain embodiments, combinations of optical radiation in variousbands of interest. For example, in some embodiments, for analytes likeglucose, the emitter 104 can emit optical radiation at three (3) or morewavelengths between about 1600 nm to about 1700 nm. In particular, theemitter 104 can emit optical radiation at or about 1610 nm, about 1640nm, and about 1665 nm. In some circumstances, the use of threewavelengths within about 1600 nm to about 1700 nm enable sufficient SNRsof about 100 dB, which can result in a measurement accuracy of about 20mg/DL or better for analytes like glucose.

In other embodiments, the emitter 104 can use two (2) wavelengths withinabout 1600 nm to about 1700 nm to advantageously enable SNRs of about 85dB, which can result in a measurement accuracy of about 25-30 mg/DL orbetter for analytes like glucose. Furthermore, in some embodiments, theemitter 104 can emit light at wavelengths above about 1670 nm.Measurements at these wavelengths can be advantageously used tocompensate or confirm the contribution of protein, water, and othernon-hemoglobin species exhibited in measurements for analytes likeglucose conducted between about 1600 nm and about 1700 nm. Of course,other wavelengths and combinations of wavelengths can be used to measureanalytes and/or to distinguish other types of tissue, fluids, tissueproperties, fluid properties, combinations of the same or the like.

For example, the emitter 104 can emit optical radiation across otherspectra for other analytes. In particular, the emitter 104 can employlight wavelengths to measure various blood analytes or percentages(e.g., saturation) thereof. For example, in one embodiment, the emitter104 can emit optical radiation in the form of pulses at wavelengthsabout 905 nm, about 1050 nm, about 1200 nm, about 1300 nm, about 1330nm, about 1610 nm, about 1640 nm, and about 1665 nm. In anotherembodiment, the emitter 104 can emit optical radiation ranging fromabout 860 nm to about 950 nm, about 950 nm to about 1100 nm, about 1100nm to about 1270 nm, about 1250 nm to about 1350 nm, about 1300 nm toabout 1360 nm, and about 1590 nm to about 1700 nm. Of course, theemitter 104 can transmit any of a variety of wavelengths of visible ornear-infrared optical radiation.

Due to the different responses of analytes to the different wavelengths,certain embodiments of the data collection system 100 can advantageouslyuse the measurements at these different wavelengths to improve theaccuracy of measurements. For example, the measurements of water fromvisible and infrared light can be used to compensate for waterabsorbance that is exhibited in the near-infrared wavelengths.

As briefly described above, the emitter 104 can include sets oflight-emitting diodes (LEDs) as its optical source. The emitter 104 canuse one or more top-emitting LEDs. In particular, in some embodiments,the emitter 104 can include top-emitting LEDs emitting light at about850 nm to 1350 nm.

The emitter 104 can also use super luminescent LEDs (SLEDs) orside-emitting LEDs. In some embodiments, the emitter 104 can employSLEDs or side-emitting LEDs to emit optical radiation at about 1600 nmto about 1800 nm. Emitter 104 can use SLEDs or side-emitting LEDs totransmit near infrared optical radiation because these types of sourcescan transmit at high power or relatively high power, e.g., about 40 mWto about 100 mW. This higher power capability can be useful tocompensate or overcome the greater attenuation of these wavelengths oflight in tissue and water. For example, the higher power emission caneffectively compensate and/or normalize the absorption signal for lightin the mentioned wavelengths to be similar in amplitude and/or effect asother wavelengths that can be detected by one or more photodetectorsafter absorption. Alternatively, the emitter 104 can use other types ofsources of optical radiation, such as a laser diode, to emitnear-infrared light into the measurement site 102.

In addition, in some embodiments, in order to assist in achieving acomparative balance of desired power output between the LEDs, some ofthe LEDs in the emitter 104 can have a filter or covering that reducesand/or cleans the optical radiation from particular LEDs or groups ofLEDs. For example, since some wavelengths of light can penetrate throughtissue relatively well, LEDs, such as some or all of the top-emittingLEDs can use a filter or covering, such as a cap or painted dye. Thiscan be useful in allowing the emitter 104 to use LEDs with a higheroutput and/or to equalize intensity of LEDs.

The data collection system 100 also includes a driver 111 that drivesthe emitter 104. The driver 111 can be a circuit or the like that iscontrolled by the monitor 109. For example, the driver 111 can providepulses of current to the emitter 104. In an embodiment, the driver 111drives the emitter 104 in a progressive fashion, such as in analternating manner. The driver 111 can drive the emitter 104 with aseries of pulses of about 1 milliwatt (mW) for some wavelengths that canpenetrate tissue relatively well and from about 40 mW to about 100 mWfor other wavelengths that tend to be significantly absorbed in tissue.A wide variety of other driving powers and driving methodologies can beused in various embodiments.

The driver 111 can be synchronized with other parts of the sensor 101and can minimize or reduce jitter in the timing of pulses of opticalradiation emitted from the emitter 104. In some embodiments, the driver111 is capable of driving the emitter 104 to emit optical radiation in apattern that varies by less than about 10 parts-per-million.

The detectors 106 capture and measure light from the measurement site102. For example, the detectors 106 can capture and measure lighttransmitted from the emitter 104 that has been attenuated or reflectedfrom the tissue in the measurement site 102. The detectors 106 canoutput a detector signal 107 responsive to the light captured ormeasured. The detectors 106 can be implemented using one or morephotodiodes, phototransistors, or the like.

In addition, the detectors 106 can be arranged with a spatialconfiguration to provide a variation of path lengths among at least someof the detectors 106. That is, some of the detectors 106 can have thesubstantially, or from the perspective of the processing algorithm,effectively, the same path length from the emitter 104. However,according to an embodiment, at least some of the detectors 106 can havea different path length from the emitter 104 relative to other of thedetectors 106. Variations in path lengths can be helpful in allowing theuse of a bulk signal stream from the detectors 106.

The front end interface 108 provides an interface that adapts the outputof the detectors 106, which is responsive to desired physiologicalparameters. For example, the front end interface 108 can adapt a signal107 received from one or more of the detectors 106 into a form that canbe processed by the monitor 109, for example, by a signal processor 110in the monitor 109. The front end interface 108 can have its componentsassembled in the sensor 101, in the monitor 109, in connecting cabling(if used), combinations of the same, or the like. The location of thefront end interface 108 can be chosen based on various factors includingspace desired for components, desired noise reductions or limits,desired heat reductions or limits, and the like.

Signal processor 110 may comprise an input component, a calculationcomponent, and an output component. The input component may beconfigured to receive measurement data 107, such as measured inputvalues, from the physiological sensor 101. The calculation component maybe configured to calculate a predicted parameter value from themeasurement data. The output component may be configured to provide anindication to the user to remove and replace the physiological sensor atleast one time, for example by displaying a prompt in the user interface112.

The front end interface 108 can be coupled to the detectors 106 and tothe signal processor 110 using a bus, wire, electrical or optical cable,flex circuit, or some other form of signal connection. The front endinterface 108 can also be at least partially integrated with variouscomponents, such as the detectors 106. For example, the front endinterface 108 can include one or more integrated circuits that are onthe same circuit board as the detectors 106. Other configurations canalso be used.

The front end interface 108 can be implemented using one or moreamplifiers, such as transimpedance amplifiers, that are coupled to oneor more analog to digital converters (ADCs) (which can be in the monitor109), such as a sigma-delta ADC. A transimpedance-based front endinterface 108 can employ single-ended circuitry, differential circuitry,and/or a hybrid configuration. A transimpedance-based front endinterface 108 can be useful for its sampling rate capability and freedomin modulation/demodulation algorithms. For example, this type of frontend interface 108 can advantageously facilitate the sampling of the ADCsbeing synchronized with the pulses emitted from the emitter 104.

The ADC or ADCs can provide one or more outputs into multiple channelsof digital information for processing by the signal processor 110 of themonitor 109. Each channel can correspond to a signal output from adetector 106.

In some embodiments, a programmable gain amplifier (PGA) can be used incombination with a transimpedance-based front end interface 108. Forexample, the output of a transimpedance-based front end interface 108can be output to a PGA that is coupled with an ADC in the monitor 109. APGA can be useful in order to provide another level of amplification andcontrol of the stream of signals from the detectors 106. Alternatively,the PGA and ADC components can be integrated with thetransimpedance-based front end interface 108 in the sensor 101.

In another embodiment, the front end interface 108 can be implementedusing switched-capacitor circuits. A switched-capacitor-based front endinterface 108 can be useful for, in certain embodiments, itsresistor-free design and analog averaging properties. In addition, aswitched-capacitor-based front end interface 108 can be useful becauseit can provide a digital signal to the signal processor 110 in themonitor 109.

As shown in FIG. 1, the monitor 109 can include the signal processor 110and a user interface, such as a display 112. The monitor 109 can alsoinclude optional outputs alone or in combination with the display 112,such as a storage device 114 and a network interface 116. In anembodiment, the signal processor 110 includes processing logic thatdetermines measurements for desired analytes, such as glucose, based onthe signals received from the detectors 106. The signal processor 110can be implemented using one or more microprocessors or subprocessors(e.g., cores), digital signal processors, application specificintegrated circuits (ASICs), field programmable gate arrays (FPGAs),combinations of the same, and the like.

The signal processor 110 can provide various signals that control theoperation of the sensor 101. For example, the signal processor 110 canprovide an emitter control signal to the driver 111. This control signalcan be useful in order to synchronize, minimize, or reduce jitter in thetiming of pulses emitted from the emitter 104. Accordingly, this controlsignal can be useful in order to cause optical radiation pulses emittedfrom the emitter 104 to follow a precise timing and consistent pattern.For example, when a transimpedance-based front end interface 108 isused, the control signal from the signal processor 110 can providesynchronization with the ADC in order to avoid aliasing, cross-talk, andthe like. As also shown, an optional memory 113 can be included in thefront-end interface 108 and/or in the signal processor 110. This memory113 can serve as a buffer or storage location for the front-endinterface 108 and/or the signal processor 110, among other uses.

The user interface 112 can provide an output, e.g., on a display, forpresentation to a user of the data collection system 100. The userinterface 112 can be implemented as a touch-screen display, an LCDdisplay, an organic LED display, or the like. In addition, the userinterface 112 can be manipulated to allow for measurement on thenon-dominant side of patient. For example, the user interface 112 caninclude a flip screen, a screen that can be moved from one side toanother on the monitor 109, or can include an ability to reorient itsdisplay indicia responsive to user input or device orientation. Incertain embodiments, the user interface 112 may present the user withthe option to take multiple measurements. For example, the user may beprompted to reapply the sensor 101 and perform an additional measurementor multiple additional measurements. The user interface 112 may indicatewhether a measurement was likely to be erroneous, and may request thatthe user take another measurement. In alternative embodiments, the datacollection system 100 can be provided without a user interface 112 andcan simply provide an output signal to a separate display or system.

A storage device 114 and a network interface 116 represent otheroptional output connections that can be included in the monitor 109. Thestorage device 114 can include any computer-readable medium, such as amemory device, hard disk storage, EEPROM, flash drive, or the like. Thevarious software and/or firmware applications can be stored in thestorage device 114, which can be executed by the signal processor 110 oranother processor of the monitor 109. The network interface 116 can be aserial bus port (RS-232/RS-485), a Universal Serial Bus (USB) port, anEthernet port, a wireless interface (e.g., WiFi such as any 802.1xinterface, including an internal wireless card), or other suitablecommunication device(s) that allows the monitor 109 to communicate andshare data with other devices. The monitor 109 can also include variousother components not shown, such as a microprocessor, graphicsprocessor, or controller to output the user interface 112, to controldata communications, to compute data trending, or to perform otheroperations.

Although not shown in the depicted embodiment, the data collectionsystem 100 can include various other components or can be configured indifferent ways. For example, the sensor 101 can have both the emitter104 and detectors 106 on the same side of the measurement site 102 anduse reflectance to measure analytes. The data collection system 100 canalso include a sensor that measures the power of light emitted from theemitter 104. The data collection system 100 may also be configured tosupport measurements at a plurality of measurement sites.

FIG. 2 illustrates an example of a monitoring device 200. In thedepicted embodiment, the monitoring device 200 includes a finger clipsensor 201 connected to a monitor 209 via a cable 212. In the embodimentshown, the monitor 209 b includes a display 210, control buttons 208 anda power button. Moreover, the monitor 209 can advantageously includeelectronic processing, signal processing, and data storage devicescapable of receiving signal data from said sensor 201, processing thesignal data to determine one or more output measurement valuesindicative of one or more physiological parameters of a monitoredpatient, and displaying the measurement values, trends of themeasurement values, combinations of measurement values, and the like.

The cable 212 connecting the sensor 201 and the monitor 209 can beimplemented using one or more wires, optical fiber, flex circuits, orthe like. In some embodiments, the cable 212 can employ twisted pairs ofconductors in order to minimize or reduce cross-talk of data transmittedfrom the sensor 201 to the monitor 209. Various lengths of the cable 212can be employed to allow for separation between the sensor 201 and themonitor 209. The cable 212 can be fitted with a connector (male orfemale) on either end of the cable 212 so that the sensor 201 and themonitor 209 can be connected and disconnected from each other.Alternatively, the sensor 201 and the monitor 209 can be coupledtogether via a wireless communication link, such as an infrared link,radio frequency channel, or any other wireless communication protocoland channel.

The monitor 209 can be attached to the patient. For example, the monitor209 can include a belt clip or straps that facilitate attachment to apatient's belt, arm, leg, or the like. The monitor 209 can also includea fitting, slot, magnet, LEMO snap-click connector, or other connectingmechanism to allow the cable 212 and sensor 201 to be attached to themonitor 209.

The monitor 209 can also include other components, such as a speaker,power button, removable storage or memory (e.g., a flash card slot), anAC power port, and one or more network interfaces, such as a universalserial bus interface or an Ethernet port. For example, the monitor 209can include a display 210 that can indicate a measurement for glucose,for example, in mg/dL. Other analytes and forms of display can alsoappear on the monitor 209.

In addition, although a single sensor 201 with a single monitor 209 isshown, different combinations of sensors and device pairings can beimplemented. For example, multiple sensors can be provided for aplurality of differing patient types or measurement sites or evenpatient fingers.

FIG. 3 shows a block diagram of a multiple measurement mode havingmultiple measurement stages in a physiological sensor system. At block310, the sensor is applied to a measurement site and the user can beprompted with instructions. The instructions can include an overview ofthe multiple measurement process. At block 320, a measurement is taken.After the measurement is taken, at block 330, it is determined whetheran additional measurement should be taken. The user may be provided withinstructions for taking an additional measurement. For example, the usermay optionally be prompted at block 340 to remove and replace the sensorbefore continuing. The user can be prompted to remove and replace thesensor using visual, audio, or physical cues, and the measurementprocess can be suspended until the sensor is replaced. In someembodiments, the user can indicate that the sensor has been replaced bypressing a button or tapping a touch screen. Although optional, incertain embodiments reapplying the sensor before taking an additionalmeasurement may be beneficial for reducing the chance of measurementerror due to an incorrectly applied sensor.

The sensor system may then loop back to blocks 320 and 330 to take ameasurement and determine whether additional measurements are needed.After a sufficient amount of measurements have been taken, the predictedparameter value can be calculated at block 350. For example, asdescribed above, where three or more measurements have been taken themedian result can be averaged with the next closest result to get afinal result. At block 360, the final result is displayed.

FIG. 4 illustrates a block diagram of a predicted parameter calculationprocess. At block 410, a physiological sensor system obtains a pluralityof input values from multiple measurements. In some embodiments, thismay be accomplished by the multiple measurement process depicted in FIG.3. The system determines at block 420 whether one or more of the inputvalues should be dropped from the input value data set. For example, themean or median measured input value can be determined, and one or moreinput values furthest from that determined value can be discarded.Additionally, measurements can be dropped based on a confidencedetermination of the measurements. For example, in a sensor systemconfigured to take three measurements, if one measurement is found tohave low confidence, that measurement can be dropped and the sensorsystem can instruct the user or care giver to take a fourth measurement.The remaining input values which are not discarded are selected at block440 for use in further calculations.

At block 430, the sensor system calculates a predicted parameter valuecorresponding to each input value. The sensor system may analyze thesepredicted parameter values at block 450 to determine whether one or moreof the predicted parameter values should be discarded. Predictedparameter values not discarded are selected at block 460 for use infurther calculations.

The sensor system at block 470 calculates the final predicted parametervalue from these multiple selected predicted parameter values (eachcorresponding to one of the multiple distinct measurements). In certainembodiments the median predicted parameter value may be selected andaveraged with the next closest predicted parameter value. In otherembodiments, various known statistical techniques, such as outlierdetection algorithms, may be used to choose, from among the predictedparameter values, the predicted parameter value that best characterizesthe distribution of parameter values. The chosen parameter value can beprovided as the final predicted parameter value. At block 480, thesystem displays the final predicted parameter value to the user and/orcaregiver.

FIG. 5 illustrates a block diagram of a dual mode sensor measurementprocess for a physiological sensor system. At block 510, the sensor isapplied to a measurement site and the user may be prompted withinstructions. The instructions may include, at block 520, an option touse a normal mode or a the multiple measurement mode. If normal mode isselected, the sensor system takes a single measurement at block 530 anduses the input value from that measurement to calculate a finalpredicted parameter value at block 540.

If the multiple measurement mode is selected, the sensor system may takea plurality of measurements at block 550. In some embodiments, this maybe accomplished by the multiple measurement process depicted in FIG. 3.For each input value corresponding to a measurement taken, the sensorsystem at block 560 may calculate a predicted parameter value. At block570, the final predicted parameter value is calculated based on one orboth of the input value data and the predicted parameter value data.Certain embodiments may employ the predicted parameter calculationprocess of FIG. 4 to calculate the final predicted parameter value. Atblock 580, the final predicted parameter value is displayed to the user.

Although the foregoing invention has been described in terms of certainpreferred embodiments, other embodiments will be apparent to those ofordinary skill in the art from the disclosure herein. Additionally,other combinations, omissions, substitutions and modifications will beapparent to the skilled artisan in view of the disclosure herein.Additionally, it is contemplated that various aspects and features ofthe invention described can be practiced separately, combined together,or substituted for one another, and that a variety of combination andsubcombinations of the features and aspects can be made and still fallwithin the scope of the invention. Furthermore, the systems describedabove need not include all of the modules and functions described in thepreferred embodiments. Accordingly, the present invention is notintended to be limited by the recitation of the preferred embodiments,but is to be defined by reference to the appended claims.

Those of skill in the art would understand that information and signalscan be represented using a variety of different technologies andtechniques. For example, data, instructions, commands, information,signals, bits, symbols, and chips that can be referenced throughout theabove description may be represented by voltages, currents,electromagnetic waves, magnetic fields or particles, optical fields orparticles, or any combination thereof.

Those of skill in the art will further appreciate that the variousillustrative logical blocks, modules, circuits, and algorithm stepsdescribed in connection with the embodiments disclosed herein can beimplemented as electronic hardware, computer software, or combinationsof both. To illustrate this interchangeability of hardware and software,various illustrative components, blocks, modules, circuits, and stepshave been described above generally in terms of their functionality.Whether such functionality is implemented as hardware or softwaredepends upon the particular application and design constraints imposedon the overall system. Skilled artisans can implement the describedfunctionality in varying ways for each particular application, but suchimplementation decisions should not be interpreted as causing adeparture from the scope of the present invention.

The various illustrative logical blocks, modules, and circuits describedin connection with the embodiments disclosed herein can be implementedor performed with a general purpose processor, a digital signalprocessor (DSP), an application specific integrated circuit (ASIC), afield programmable gate array (FPGA) or other programmable logic device,discrete gate or transistor logic, discrete hardware components, or anycombination thereof designed to perform the functions described herein.A general purpose processor can be a microprocessor, but in thealternative, the processor can be any conventional processor,controller, microcontroller, or state machine. A processor can also beimplemented as a combination of computing devices, e.g., a combinationof a DSP and a microprocessor, a plurality of microprocessors, one ormore microprocessors in conjunction with a DSP core, or any other suchconfiguration.

The steps of a method or algorithm described in connection with theembodiments disclosed herein can be embodied directly in hardware, in asoftware module executed by a processor, or in a combination of the two.A software module can reside in RAM memory, flash memory, ROM memory,EPROM memory, EEPROM memory, registers, hard disk, a removable disk, aCD-ROM, or other form of storage medium known in the art. A storagemedium is coupled to the processor, such that the processor can readinformation from, and write information to, the storage medium. In thealternative, the storage medium can be integral to the processor. Theprocessor and the storage medium can reside in an ASIC. The ASIC canreside in a user terminal. The processor and the storage medium canreside as discrete components in a user terminal.

The previous description of the disclosed embodiments is provided toenable a person skilled in the art to make or use the present invention.Various modifications to these embodiments will be readily apparent tothose skilled in the art, and the generic principles defined herein canbe applied to other embodiments without departing from the spirit orscope of the invention. Thus, the present invention is not intended tobe limited to the embodiments shown herein but is to be accorded thewidest scope consistent with the principles and novel features disclosedherein. Thus, the invention is limited only by the claims.

1. A method of providing in a physiological sensor a predicted parametervalue, the method comprising: obtaining a first set of measured inputvalues from a physiological sensor; obtaining one or more additionalsets of measured input values from the physiological sensor, whereinobtaining each of said one or more additional sets of measured inputvalues comprises reapplying the physiological sensor, and obtaining aset of measured input values; calculating a predicted parameter valuefor each of the first and additional sets of measured input values;discarding one or more of the calculated predicted parameter values;determining, from the remaining predicted parameter values, a finalpredicted parameter value; providing an indication of the finalpredicted parameter value to a user.
 2. The method of claim 1 whereinthe discarded one or more predicted parameter values are selected basedon the mean of the calculated predicted parameter values.
 3. The methodof claim 1 wherein the discarded one or more predicted parameter valuesare selected based on the median of the calculated predicted parametervalues.
 4. A method of providing in a physiological sensor a predictedparameter value, the method comprising: applying a physiological sensorconfigured to obtain one or more measured input values; obtaining afirst measured input value; reapplying the physiological sensor;obtaining an additional measured input value; determining a finalpredicted parameter value; and providing an indication of the finalpredicted parameter value to a user.
 5. The method of claim 4, furthercomprising calculating a predicted parameter value for each of themeasured input values.
 6. The method of claim 5, further comprisingdiscarding one or more of the calculated predicted parameter values. 7.The method of claim 5, wherein determining the final predicted parametervalue is accomplished by averaging the calculated predicted parametervalues.
 8. The method of claim 5, further comprising: determining amedian predicted parameter value and a next closest predicted parametervalue of the calculated predicted parameter values; and whereindetermining the final predicted parameter value is accomplished byaveraging the median predicted parameter value with the next closestpredicted parameter value.
 9. The method of claim 5, wherein determiningthe final predicted parameter value is accomplished by selecting fromamong the calculated predicted parameter values a single predictedparameter value that best characterizes the distribution of thecalculated parameter values.
 10. The method of claim 9, whereinselecting the single predicted parameter value is accomplished by anoutlier detection algorithm.
 11. A system for determining a predictedparameter value comprising: a physiological sensor configured to beapplied to a measurement site by a user; and a processor comprising: aninput component configured to receive at least one measured input valuefrom the physiological sensor; a calculation component configured tocalculate a predicted parameter value, and an output componentconfigured to provide an indication to the user to remove and replacethe physiological sensor at least one time.
 12. The system of claim 11,wherein the indication comprises a sound.
 13. The system of claim 11,wherein the indication comprises a light.
 14. The system of claim 11,wherein the indication comprises a visual prompt in a touch screen userinterface.
 15. The system of claim 11, wherein the user can indicatethat the sensor has been replaced by pressing a button.
 16. The systemof claim 11, further comprising a touch screen interface, wherein theuser can indicate that the sensor has been replaced by interacting withthe touch screen.
 17. The system of claim 11, wherein the processorprovides the indication to the user to remove and replace the sensorthree times.